Advertisement for orthosearch.org.uk
Results 1 - 3 of 3
Results per page:
The Bone & Joint Journal
Vol. 103-B, Issue 12 | Pages 1754 - 1758
1 Dec 2021
Farrow L Zhong M Ashcroft GP Anderson L Meek RMD

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines. Cite this article: Bone Joint J 2021;103-B(12):1754–1758


The Bone & Joint Journal
Vol. 104-B, Issue 8 | Pages 911 - 914
1 Aug 2022
Prijs J Liao Z Ashkani-Esfahani S Olczak J Gordon M Jayakumar P Jutte PC Jaarsma RL IJpma FFA Doornberg JN

Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’).

Cite this article: Bone Joint J 2022;104-B(8):911–914.


The Bone & Joint Journal
Vol. 104-B, Issue 10 | Pages 1104 - 1109
1 Oct 2022
Hansjee S Giebaly DE Shaarani SR Haddad FS

We aim to explore the potential technologies for monitoring and assessment of patients undergoing arthroplasty by examining selected literature focusing on the technology currently available and reflecting on possible future development and application. The reviewed literature indicates a large variety of different hardware and software, widely available and used in a limited manner, to assess patients’ performance. There are extensive opportunities to enhance and integrate the systems which are already in existence to develop patient-specific pathways for rehabilitation.

Cite this article: Bone Joint J 2022;104-B(10):1104–1109.